DAIKON

Data Acquisition, Integration, and Knowledge Capture Web Application

Conventional methods of organizing data face challenges in meeting the extensive scale and uniformity required for collaborative endeavors in drug discovery. In response to this challenge and with the aim of enhancing data sharing and coordination, we have developer DAIKON—an open-source framework seamlessly integrating targets, screens, hits, and project management within the domain of target-based drug discovery portfolios.

The knowledge capture components of this framework empower teams to document the evolving properties of molecules, foster collaboration through discussion threads, and incorporate visual modules that illustrate target progress through the pipeline. Functioning as a repository, DAIKON aggregates data from Mycobrowser, UniProt, and PDB, seeking to standardize diverse drug discovery programs on a global scale while accommodating local workflow nuances.

References – ACS Pharmacology & Translational Science 2023 6 (7), 1043-1051 DOI: 10.1021/acsptsci.3c00034

Figure 1. DAIKON Modules

The application attains modularity by abstracting the database, creating separate layers for entities, business logic, infrastructure, APIs, and frontend. Docker facilitates the packaging of the framework into two solutions: daikon-server-core and daikon-client. Organizations possess the flexibility to deploy the project on on-premises servers or VPCs, with Active Directory/SSO support for streamlined user administration. End users can conveniently access the application through a web browser.

It functions as a comprehensive tool for overseeing the drug discovery process, assisting from target identification to pre-clinical development.

  • Data Capture and Organization: It offers a centralized platform for capturing and organizing drug discovery data, encompassing experimental data. Users can store, search, and retrieve data in a structured manner.
  • Project Management: It incorporates project management features, facilitating teams in tracking progress, managing tasks, and collaborating efficiently. It allows users to set milestones, assign tasks, and monitor project advancement.
  • Collaboration: It fosters collaboration among team members by providing a platform for real-time communication and knowledge sharing. Users can exchange feedback, share data, and interact seamlessly.
  • Data Analysis: It includes features for data analysis, aiding users in making informed decisions about drug development. The tool provides visualization and analysis tools to identify trends and patterns in the data.
Figure 2. Typical TB drug discovery workflow in DAIKON.

We plan to have DAIKON as an interface for scientists in TBSGC, the Steering Committee and the NIAID Structural Genomics Centers for Infectious Diseases, to maximize efficiency and reduce redundancy in the early stages of drug discovery.